1,720,959 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
SpecAugment for Sound Event Detection in Domestic Environments using Ensemble of Convolutional Recurrent Neural Networks
Get PDFIn this paper, we present a method to detect sound events in domestic environments using small weakly labeled data, large unlabeled data, and strongly labeled synthetic data as proposed in the Detection and Classification of Acoustic Scenes and Events 2019 Challenge task 4. To solve the problem, we use a convolutional recurrent neural network composed of stacks of convolutional neural networks and bi-directional gated recurrent units. Moreover, we propose various methods such as SpecAugment, event activity detection, multi-median filtering, mean-teacher model, and an ensemble of neural networks to improve performance. By combining the proposed methods, sound event detection performance can be enhanced, compared with the baseline algorithm. Consequently, performance evaluation shows that the proposed method provides detection results of 40.89% for event-based metrics and 66.17% for segment-based metrics. For the evaluation dataset, the performance was 34.4% for event-based metrics and 66.4% for segment-based metrics.12913
멀티모달 심층 신경망을 이용한 시각 정보 기반 공간 오디오 생성 및 향상
No full text학위논문(박사) - 한국과학기술원 : 문화기술대학원, 2025.2,[iv, 81 p. :]Spatial audio is essential for many immersive content serviceshowever, it is challenging to obtain or create it. Therefore, to provide a wide range of spatial audio services, leveraging existing audio content to create new spatial audio content can be an effective solution. To address this requirement, this study proposed a method for generating and enhancing spatial audio based on visual information using multi-modal deep neural networks. Recently, multi-modal based ambisonic audio generation has emerged as a promising approach for spatial audio generation. It combines multiple modalities, such as audio and video, and provides more intuitive control of ambisonic audio generation. Moreover, it leverages the advantages of machine-learning methods to automatically learn the correlation between different features and generate high-quality ambisonic sounds. Herein, we propose a separation- and localization-based spatial audio generation model. First, the network extracts visual features and separates audio into sound sources. Then, it conducts localization by mapping the separated sound sources to the visual features. To overcome the performance limitation of the previous self-supervised source separation approach, we employ a pre-trained source separator with superior performance. To improve the localization performance further, we propose a channel panning loss function between each channel of the ambisonic signal. We use three different types of datasets to train the model experimentally and evaluate the proposed method with four metrics. The results show that the proposed model achieves better spatialization performance than the baseline models. In addition, we present audio dereverberation based on the visually-informed diffusion model (ADVID), a novel method that leverages visual information to enhance the quality and intelligibility of speech in reverberant environments. Traditional audio dereverberation techniques perform poorly in complex acoustic settings because of their reliance solely on audio signals. By incorporating visual cues, ADVID effectively captures the spatial and material properties of an acoustic scene, thereby improving the dereverberation performance. ADVID utilizes pretrained visual encoder architectures to extract detailed visual features from red, green, and blue (RGB) and depth images. These features provide a crucial environmental context, including the geometry and material composition essential for accurate dereverberation. Our approach integrates a diffusion model based on the noise conditional score network architecture, which is enhanced by a multi-resolution U-Net framework and cross-modal attention mechanisms. Thus, the model is enabled to robustly process complex spectrograms and achieve superior dereverberation results. Moreover, to ensure alignment between the visual and audio embeddings, we introduce a contrastive audio-visual matching loss that further enhances the effectiveness of the model. Further, the performance was experimentally evaluated using audio-visual datasets. The results demonstrate that ADVID significantly outperforms various state-of-the-art methods, achieving higher scores on objective metrics. Subjective listening tests also confirmed that they provided superior speech quality and intelligibility compared with the baseline model. In addition, the feasibility of the proposed model for providing spatial audio content was validated by resynthesizing the target spatial environment from the dereverberated audio. Finally, we validated the performance of the proposed model through experiments using a dataset obtained from a real-world environment, confirming its extensibility.한국과학기술원 :문화기술대학원
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Ultra-Low Power Circuit Design for Miniaturized IoT Platform
Get PDFThis thesis examines the ultra-low power circuit techniques for mm-scale Internet of Things (IoT) platforms. The IoT devices are known for their small form factors and limited battery capacity and lifespan. So, ultra-low power consumption of always-on blocks is required for the IoT devices that adopt aggressive duty-cycling for high power efficiency and long lifespan. Several
problems need to be addressed regarding IoT device designs, such as ultra-low power circuit design techniques for sleep mode and energy-efficient and fast data rate transmission for active mode communication. Therefore, this thesis highlights the ultra-low power always-on systems, focusing on energy efficient optical transmission in order to miniaturize the IoT systems.
First, this thesis presents a battery-less sub-nW micro-controller for an always-operating system implemented with a newly proposed logic family.
Second, it proposes an always-operating sub-nW light-to-digital converter to measure instant light intensity and cumulative light exposure, which employs the characteristics of this proposed logic family. Third, it presents an ultra-low
standby power optical wake-up receiver with ambient light canceling using dual-mode operation.
Finally, an energy-efficient low power optical transmitter for an implantable IoT device is suggested. Implications for future research are also provided.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/145862/1/imhotep_1.pd
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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